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  • 1
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 40, No. 16_suppl ( 2022-06-01), p. e17006-e17006
    Abstract: e17006 Background: In 2021, national data between the Decipher 22-gene prognostic gene expression classifier (GC) for men with prostate cancer and the Surveillance, Epidemiology, and End Results (SEER) cancer registries were linked. The purpose of the work is to report on the linkage by characterizing national GC usage and its association with treatment decisions for men with prostate cancer. Methods: Patients in the SEER registries with primary prostate cancer diagnosis from 2010 to 2018 were included and linked to data from GC testing conducted between 2014 to 2020 (Veracyte, San Diego, CA). GC scores (range 0-1) and GC risk groups (low, intermediate, and high) were used for continuous and categorical analyses. Multivariable logistic regression was used to quantify the association between GC and active surveillance and watchful waiting (AS/WW) use and adverse pathology at radical prostatectomy (RP). Adverse pathology was defined as pathological grade group ≥3, pathological stage ≥pT3b, or lymph node invasion. Results: A total of 575,363 patients were eligible for analysis, of which 10,528 patients underwent GC testing (5,015 GC biopsy test, and 5,513 GC RP test). The median age was 67 for both tested and untested, but more white patients underwent testing (82% vs 76%, p 〈 0.001). For GC biopsy tested patients, AS/WW was highest for those with GC low risk results (41%) as compared to those with intermediate (32%) or high (17%) GC risk (p 〈 0.001). RP rates were lower in the tested compared to untested (25% vs. 36%, p 〈 0.001), and among the tested patients, RP use increased by GC risk group (19% of low, 25% of intermediate, and 34% of high GC risk, p 〈 0.001). A similar trend by GC risk group in management for radiation therapy was observed (13% of low, 19% of intermediate, and 29% of high GC risk, p 〈 0.001). In a multivariable logistic regression adjusted for age, race, NCCN risk group, and year of diagnosis, GC tested patients were more likely to undergo AS/WW compared to untested (OR 2.9 [95% CI, 2.8-3.1], p 〈 0.001). Within the subset of patients classified as NCCN low/favorable intermediate risk at biopsy and who were subsequently treated with RP (n = 594), GC high risk ( 〉 0.6) was associated with more than 3 times the odds of harboring adverse pathology (OR 3.2 [95% CI 1.6-6.4], p 〈 0.001). Conclusions: Using the first ever linked SEER-Decipher data, we demonstrate that population-based treatment patterns are independently associated with GC test results. Patients with lower GC scores are independently more likely to undergo AS/WW; those with higher scores are more likely to have adverse pathology at time of RP.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2022
    detail.hit.zdb_id: 2005181-5
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  • 2
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 6_suppl ( 2023-02-20), p. 299-299
    Abstract: 299 Background: Recently, an MMAI prognostic biomarker, ArteraAI Prostate, was trained and validated in localized prostate cancer to more accurately risk stratify patients for multiple endpoints compared to NCCN risk groups (Esteva et al., 2022). Prognostication within an NCCN risk group remains clinically important given the multiple treatment decisions required within each risk group (e.g., radiotherapy dose or hormone therapy use). Herein, we validated the MMAI biomarker in high-risk prostate cancer where an increasing number of therapeutic decisions is required. Methods: This study leveraged histopathology image and clinical data from patients with at least one high-risk feature (HRF; cT3-cT4, Gleason 8-10, PSA 〉 20 ng/mL, primary Gleason pattern 5) from six NRG/RTOG phase III randomized trials (n=1,088). Patients from two trials not part of the initial MMAI biomarker training/validation (RTOG 0521 [n=344] and 9902 [n=318] ) and the MMAI validation cohort (RTOG 9202, 9408, 9413, and 9910 [n=426]) were included. Fine-Gray, cumulative incidence, and time dependent area under the curve (tdAUC) analyses were performed for time to distant metastasis (DM) and prostate cancer-specific mortality (PCSM) for standard clinicopathologic variables (age, PSA, Gleason score, T-stage, number of HRFs) and the MMAI model, as a continuous score (per standard deviation increase) and categorically by quartile. Death from other causes were treated as competing risks. Results: The analyzed cohort had a median follow-up of 10.4 years. Median PSA was 21 ng/mL, 60% had Gleason 8-10 disease, 37% had cT3-T4 disease, and 20% were African American. On univariable analysis, the MMAI model was significantly associated with DM (subdistribution hazard ratio [sHR] 2.05, 95% CI 1.74-2.43, p 〈 0.001) and PCSM (sHR 2.04, 95% CI 1.73-2.42, 〈 0.001). On multivariable analysis, the MMAI model, adjusting for either age, PSA, Gleason score, T-stage, or number of HRFs, was the only variable significantly associated with DM. TdAUC was highest for the MMAI biomarker for both 5-year DM (0.71), compared to PSA (0.56), Gleason score (0.61), T-stage (0.63), or number of HRFs (0.64), and for 5-year PCSM (0.75), compared to clinicopathologic variables (range 0.53-0.63). The estimated 10-year DM and 15-year PCSM rates for MMAI quartile 1 vs 4 were 8% vs 31% and 8% vs 34%, respectively. Conclusions: Our novel MMAI prognostic biomarker was successfully validated across six phase III randomized trials with long-term follow-up to be independently prognostic over standard clinical and pathologic variables for men with high-risk prostate cancer. Despite all patients having high-risk disease, the MMAI biomarker identified those with highly variable risks for DM and PCSM. This tool can help enable personalized, shared decision making for patients and providers.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
    detail.hit.zdb_id: 2005181-5
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  • 3
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. 5001-5001
    Abstract: 5001 Background: Androgen deprivation therapy (ADT) improves survival and reduces risk of metastasis in men with high-risk localized prostate cancer (PC) receiving radiotherapy (RT). Predictive biomarkers are needed to guide ADT duration to maximize benefits and minimize risks. We sought to train and validate the first predictive biomarker for long-term (LT) vs short-term (ST) ADT using multiple phase III NRG Oncology randomized trials. Methods: Pre-treatment prostate biopsy slides were digitized from six phase III NRG/RTOG randomized trials of men receiving RT +/- ADT. The artificial intelligence (AI)-derived clinical and histopathological predictive biomarker was trained on RTOG 9408, 9413, 9902, 9910, and 0521 to predict differential benefit of LTADT on distant metastasis (DM). After the AI biomarker was locked, it was validated on RTOG 9202, which randomized men to RT + STADT (4 mo) vs LTADT (28 mo). The predictive utility of the AI biomarker was evaluated for the primary and secondary endpoints of DM and PC-specific mortality (PCSM), respectively, for ADT duration with Fine-Gray interaction models. Event rates were estimated by the cumulative incidence method. Deaths from other causes were treated as competing risks. Results: The AI-derived biomarker was trained on 2,641 men (median follow-up of 9.8 years, IQR [8.2, 11.5] ) and validated on 1,192 men from RTOG 9202 (median follow-up of 17.2 years, IQR [9.1, 19.6]), where 80% had at least one high/very high (H/VH) risk feature (cT3-4, Gleason 8-10, PSA 〉 20, or primary Gleason pattern 5). Consistent with published results, LTADT significantly improved DM (subdistribution HR [sHR] 0.64, 95% CI 0.50-0.82, p 〈 0.001) in the validation cohort. The AI biomarker was prognostic for DM (sHR 2.35, 95% CI 1.72-3.19, p 〈 0.001). A significant biomarker-treatment interaction was observed (p = 0.04), in which AI-biomarker (+) men (n = 785, 66%) had reduced DM with LTADT (sHR 0.55, 95% CI 0.41-0.73, p 〈 0.001), but no benefit was observed (sHR 1.06, 95% CI 0.61-1.84, p = 0.84) for AI-biomarker (-) men (n = 407, 34%). The 10-year DM rate difference between RT + LTADT vs RT + STADT was 13% in AI-biomarker (+) men vs 2% in AI-biomarker (-) men. Similar trends were observed for PCSM outcomes. Risk classification (NCCN intermediate [n = 221, 43% (+)] vs other H/VH risk [n = 954, 71% (+)] ) was prognostic but not predictive of LTADT benefit. Conclusions: We have successfully validated the first predictive biomarker of LTADT benefit with RT in localized high-risk PC using an AI-derived digital pathology-based platform in the phase III NRG/RTOG 9202 trial. The predictive AI biomarker identified 34% of men that could derive similar benefit with STADT, avoiding the side effects of prolonged ADT, and 43% of intermediate risk men who would benefit from LTADT.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
    detail.hit.zdb_id: 2005181-5
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  • 4
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 39, No. 15_suppl ( 2021-05-20), p. 5010-5010
    Abstract: 5010 Background: GC has been shown to independently prognosticate outcomes in prostate cancer. Herein, we validate the GC in a European randomized phase III trial of dose escalated SRT after RP. Methods: SAKK 09/10 (NCT01272050) randomized 350 patients with biochemical recurrence after RP to 64Gy vs 70Gy. No patients received androgen deprivation therapy (ADT) or pelvic nodal radiotherapy. A pre-specified statistical plan was developed to assess the impact of the GC on clinical outcomes. RP samples were centrally reviewed for the highest-grade tumor and those passing quality control (QC) were run on a clinical-grade whole-transcriptome assay to obtain the GC score (0 to 1; 〈 0.45, 0.45-0.6, 〉 0.6 for low-, intermediate-, and high, respectively). The primary aim of this study was to validate the GC for the prediction of freedom from biochemical progression (FFBP) using Cox multivariable analysis (MVA) adjusting for age, T-category, Gleason score, persistent PSA after RP, PSA at randomization, and randomization arm. The secondary aims were to evaluate the association of GC with clinical progression-free survival (CPFS) and use of salvage ADT. Results: Of 233 patients with tissue available, 226 passed QC and were included for analysis. The final GC cohort was a representative sample of the overall cohort, with a median follow-up of 6.3 years (IQR 6.0-7.2). GC score (continuous per 0.1 unit, score 0-1) was independently associated with FFBP (HR 1.14 [95% CI 1.03-1.25], p = 0.009). Higher GC scores were independently associated with CPFS, use of salvage ADT, and rapid biochemical failure ( 〈 18 months after SRT). High- vs. low/intermediate-GC showed a HR of 2.22 ([95% CI 1.37-3.58], p = 0.001) for FFBP, 2.29 ([95% CI 1.32-3.98] , p = 0.003) for CPFS, and 2.99 ([95% CI 1.50-5.95], p = 0.002) for use of salvage ADT. Patients with high-GC had 5-year FFBP of 45% [95% CI 32-59] vs 71% [95% CI 64-78] in low-intermediate GC. Similar estimates for GC risk groups were observed in the 64Gy vs 70Gy in GC high (5-year FFBP of 51% [95% CI 32-70] vs 39% [95% CI 20-59]) and in low-intermediate GC (75% [95% CI 65-84] vs 69% [95% CI 59-78]). Conclusions: This study represents the first contemporary randomized controlled trial in patients with recurrent prostate cancer treated with early SRT without ADT that has validated the prognostic utility of the GC. Independent of standard clinicopathologic variables and radiotherapy dose, patients with a high-GC were more than twice as likely than a lower GC score to experience biochemical and clinical progression and receive salvage ADT. This data confirms the clinical value of Decipher GC for tailoring treatment in the postoperative salvage setting.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2021
    detail.hit.zdb_id: 2005181-5
    Library Location Call Number Volume/Issue/Year Availability
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